scholarly journals A Network-Centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers

2021 ◽  
Vol 12 ◽  
Author(s):  
Rafsan Ahmed ◽  
Cesim Erten ◽  
Aissa Houdjedj ◽  
Hilal Kazan ◽  
Cansu Yalcin
Keyword(s):  
Simulated Data ◽  
Driver Gene ◽  
Interaction Patterns ◽  
Cancer Genes ◽  
Mutation Load ◽  
Mutual Exclusivity ◽  
Cancer Driver ◽  
Tumor Subtypes ◽  
Main Components ◽  
Main Component

One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same molecular pathway. Several ME tests have been proposed recently, however the current protocols to evaluate ME tests have two main limitations. Firstly the evaluations are mostly with respect to simulated data and secondly the evaluation metrics lack a network-centric view. The latter is especially crucial as the notion of common functionality can be achieved through searching for interaction patterns in relevant networks. We propose a network-centric framework to evaluate the pairwise significances found by statistical ME tests. It has three main components. The first component consists of metrics employed in the network-centric ME evaluations. Such metrics are designed so that network knowledge and the reference set of known cancer genes are incorporated in ME evaluations under a careful definition of proper control groups. The other two components are designed as further mechanisms to avoid confounders inherent in ME detection on top of the network-centric view. To this end, our second objective is to dissect the side effects caused by mutation load artifacts where mutations driving tumor subtypes with low mutation load might be incorrectly diagnosed as mutually exclusive. Finally, as part of the third main component, the confounding issue stemming from the use of nonspecific interaction networks generated as combinations of interactions from different tissues is resolved through the creation and use of tissue-specific networks in the proposed framework. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/NetCentric.

scholarly journals A Network-centric Framework for the Evaluation of Mutual Exclusivity Tests on Cancer Drivers

2021 ◽  
Author(s):  
Rafsan Ahmed ◽  
Cesim Erten ◽  
Aissa Houdjedj ◽  
Hilal Kazan ◽  
Cansu Yalcin
Keyword(s):  
Simulated Data ◽  
Driver Gene ◽  
Interaction Patterns ◽  
Cancer Genes ◽  
Mutation Load ◽  
Mutual Exclusivity ◽  
Cancer Driver ◽  
Tumor Subtypes ◽  
Main Components ◽  
Main Component

One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same molecular pathway. Several ME tests have been proposed recently, however the current protocols to evaluate ME tests have two main limitations. Firstly the evaluations are mostly with respect to simulated data and secondly the evaluation metrics lack a network-centric view. The latter is especially crucial as the notion of common functionality can be achieved through searching for interaction patterns in relevant networks. We propose a network-centric framework to evaluate the pairwise significances found by statistical ME tests. It has three main components. The first component consists of metrics employed in the network-centric ME evaluations. Such metrics are designed so that network knowledge and the reference set of known cancer genes are incorporated in ME evaluations under a careful definition of proper control groups. The other two components are designed as further mechanisms to avoid confounders inherent in ME detection on top of the network-centric view. To this end, our second objective is to dissect the side effects caused by mutation load artifacts where mutations driving tumor subtypes with low mutation load might be incorrectly diagnosed as mutually exclusive. Finally, as part of the third main component, the confounding issue stemming from the use of nonspecific interaction networks generated as combinations of interactions from different tissues is resolved through the creation and use of tissue-specific networks in the proposed framework. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/NetCentric.

scholarly journals Interpreting pathways to discover cancer driver genes with Moonlight

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Antonio Colaprico ◽  
Catharina Olsen ◽  
Matthew H. Bailey ◽  
Gabriel J. Odom ◽  
Thilde Terkelsen ◽  
...  
Keyword(s):  
Tumor Suppressors ◽  
Molecular Mechanisms ◽  
Dual Role ◽  
Tissue Type ◽  
Driver Gene ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Therapeutic Decisions ◽  
Cancer Driver Genes

AbstractCancer driver gene alterations influence cancer development, occurring in oncogenes, tumor suppressors, and dual role genes. Discovering dual role cancer genes is difficult because of their elusive context-dependent behavior. We define oncogenic mediators as genes controlling biological processes. With them, we classify cancer driver genes, unveiling their roles in cancer mechanisms. To this end, we present Moonlight, a tool that incorporates multiple -omics data to identify critical cancer driver genes. With Moonlight, we analyze 8000+ tumor samples from 18 cancer types, discovering 3310 oncogenic mediators, 151 having dual roles. By incorporating additional data (amplification, mutation, DNA methylation, chromatin accessibility), we reveal 1000+ cancer driver genes, corroborating known molecular mechanisms. Additionally, we confirm critical cancer driver genes by analysing cell-line datasets. We discover inactivation of tumor suppressors in intron regions and that tissue type and subtype indicate dual role status. These findings help explain tumor heterogeneity and could guide therapeutic decisions.

scholarly journals MEXCOwalk: mutual exclusion and coverage based random walk to identify cancer modules

2019 ◽  
Author(s):  
Rafsan Ahmed ◽  
Ilyes Baali ◽  
Cesim Erten ◽  
Evis Hoxha ◽  
Hilal Kazan
Keyword(s):  
Random Walk ◽  
Supplementary Information ◽  
Risk Scores ◽  
Cancer Genes ◽  
Mutual Exclusivity ◽  
Cancer Driver ◽  
Cancer Data ◽  
Ppi Networks ◽  
Cancer Types ◽  
Pan Cancer

Abstract Motivation Genomic analyses from large cancer cohorts have revealed the mutational heterogeneity problem which hinders the identification of driver genes based only on mutation profiles. One way to tackle this problem is to incorporate the fact that genes act together in functional modules. The connectivity knowledge present in existing protein–protein interaction (PPI) networks together with mutation frequencies of genes and the mutual exclusivity of cancer mutations can be utilized to increase the accuracy of identifying cancer driver modules. Results We present a novel edge-weighted random walk-based approach that incorporates connectivity information in the form of protein–protein interactions (PPIs), mutual exclusivity and coverage to identify cancer driver modules. MEXCOwalk outperforms several state-of-the-art computational methods on TCGA pan-cancer data in terms of recovering known cancer genes, providing modules that are capable of classifying normal and tumor samples and that are enriched for mutations in specific cancer types. Furthermore, the risk scores determined with output modules can stratify patients into low-risk and high-risk groups in multiple cancer types. MEXCOwalk identifies modules containing both well-known cancer genes and putative cancer genes that are rarely mutated in the pan-cancer data. The data, the source code and useful scripts are available at: https://github.com/abu-compbio/MEXCOwalk. Supplementary information Supplementary data are available at Bioinformatics online.

OIL CONTENT AND CHEMICAL COMPOSITION IN THE PARTS OF OIL PALM FRUIT FROM 8 IOPRI VARIETIES

2018 ◽  
Vol 24 (2) ◽  
pp. 67-76
Author(s):  
Sujadi Sujadi ◽  
Hasrul Abdi Hasibuan ◽  
Meta Rivani ◽  
Abdul Razak Purba
Keyword(s):  
Fatty Acid ◽  
Palmitic Acid ◽  
Oil Palm ◽  
Oil Content ◽  
Mean Value ◽  
Oleic Acid Content ◽  
Palm Fruit ◽  
Fruit Samples ◽  
Main Components ◽  
Main Component

Fresh fruit bunches (FFB) consist of fruit be composed grade in few spikelet. Fruit at a spikelet can be distinguished into performed fruit namely internal fruit, middle fruit and outer fruit as soon as each section contain parthenocarpy fruits. This research was conducted for determine composition and content fatty acid of oil at internal fruit, middle, outer and parthenocarpy fruit from oil palm fruit. Samples of fruit came from 3 – 5 spikelet the central of FFB. Result showed that oil content of outer fruit (46.9 + 9.9)% trend higher be compared middle fruit (42.8 + 10.3)% and internal fruit (39.1 + 9.5)%. Parthenocarpy fruits have a low oil content (14.2 + 16.2)% except yellowish fruit trend high relatively oil content. The main components of fatty acid at outer fruit, middle and internal are palmitic acid, oleic, linoleic and stearic with mean value respectively (44.8 – 45.8)%, (37.6 – 38.0)%, (9.9 – 10.9)% and (4.6 – 4.8)%. Oil content at parthenocarpy fruit have amount main component of fatty acid with performed fruit but composition of palmitic acid (40.0 + 5.9)% and oleic (34.6 + 8.4)% lower while linoleic acid (16.9 + 8.5)% and linolenic (1.6 + 1.8)% higher be compared to performed fruit. Simalungun variety has the highest oil content in the part of fruit, with that PPKS 540 and La Mé respectively. PPKS 540 variety has the highest oleic acid content while PPKS 718 has the highest linoleic content.

scholarly journals Ranking cancer drivers via betweenness-based outlier detection and random walks

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Cesim Erten ◽  
Aissa Houdjedj ◽  
Hilal Kazan
Keyword(s):  
Cancer Genomics ◽  
Interaction Network ◽  
Molecular Data ◽  
Alternative Methods ◽  
Patient Specific ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Protein Protein Interaction ◽  
Genomic Studies

Abstract Background Recent cancer genomic studies have generated detailed molecular data on a large number of cancer patients. A key remaining problem in cancer genomics is the identification of driver genes. Results We propose BetweenNet, a computational approach that integrates genomic data with a protein-protein interaction network to identify cancer driver genes. BetweenNet utilizes a measure based on betweenness centrality on patient specific networks to identify the so-called outlier genes that correspond to dysregulated genes for each patient. Setting up the relationship between the mutated genes and the outliers through a bipartite graph, it employs a random-walk process on the graph, which provides the final prioritization of the mutated genes. We compare BetweenNet against state-of-the art cancer gene prioritization methods on lung, breast, and pan-cancer datasets. Conclusions Our evaluations show that BetweenNet is better at recovering known cancer genes based on multiple reference databases. Additionally, we show that the GO terms and the reference pathways enriched in BetweenNet ranked genes and those that are enriched in known cancer genes overlap significantly when compared to the overlaps achieved by the rankings of the alternative methods.

scholarly journals driveR: a novel method for prioritizing cancer driver genes using somatic genomics data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ege Ülgen ◽  
O. Uğur Sezerman
Keyword(s):  
Biological Knowledge ◽  
Driver Gene ◽  
Driver Genes ◽  
Cancer Driver ◽  
Prior Biological Knowledge ◽  
Wilcoxon Rank Sum Test ◽  
Cancer Genomes ◽  
Novel Method ◽  
Cancer Driver Genes ◽  
Batch Analysis

Abstract Background Cancer develops due to “driver” alterations. Numerous approaches exist for predicting cancer drivers from cohort-scale genomics data. However, methods for personalized analysis of driver genes are underdeveloped. In this study, we developed a novel personalized/batch analysis approach for driver gene prioritization utilizing somatic genomics data, called driveR. Results Combining genomics information and prior biological knowledge, driveR accurately prioritizes cancer driver genes via a multi-task learning model. Testing on 28 different datasets, this study demonstrates that driveR performs adequately, achieving a median AUC of 0.684 (range 0.651–0.861) on the 28 batch analysis test datasets, and a median AUC of 0.773 (range 0–1) on the 5157 personalized analysis test samples. Moreover, it outperforms existing approaches, achieving a significantly higher median AUC than all of MutSigCV (Wilcoxon rank-sum test p < 0.001), DriverNet (p < 0.001), OncodriveFML (p < 0.001) and MutPanning (p < 0.001) on batch analysis test datasets, and a significantly higher median AUC than DawnRank (p < 0.001) and PRODIGY (p < 0.001) on personalized analysis datasets. Conclusions This study demonstrates that the proposed method is an accurate and easy-to-utilize approach for prioritizing driver genes in cancer genomes in personalized or batch analyses. driveR is available on CRAN: https://cran.r-project.org/package=driveR.

scholarly journals Behavioral and Antennal Responses of Tribolium confusum to Varronia globosa Essential Oil and Its Main Constituents: Perspective for Their Use as Repellent

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4393
Author(s):  
Cesar Auguste Badji ◽  
Jean Dorland ◽  
Lynda Kheloul ◽  
Dimitri Bréard ◽  
Pascal Richomme ◽  
...  
Keyword(s):  
Essential Oil ◽  
Tribolium Confusum ◽  
High Dose ◽  
Synthetic Chemicals ◽  
Stored Product Pest ◽  
Indigenous Plant ◽  
Main Components ◽  
Electroantennogram Recordings ◽  
The Individual ◽  
Main Component

Essential oils of aromatic plants represent an alternative to classical pest control with synthetic chemicals. They are especially promising for the alternative control of stored product pest insects. Here, we tested behavioral and electrophysiological responses of the stored product pest Tribolium confusum, to the essential oil of a Brazilian indigenous plant, Varronia globosa, collected in the Caatinga ecosystem. We analyzed the essential oil by GC-MS, tested the effects of the entire oil and its major components on the behavior of individual beetles in a four-way olfactometer, and investigated responses to these stimuli in electroantennogram recordings (EAG). We could identify 25 constituents in the essential oil of V. globosa, with anethole, caryophyllene and spathulenole as main components. The oil and its main component anethole had repellent effects already at low doses, whereas caryophyllene had only a repellent effect at a high dose. In addition, the essential oil abolished the attractive effect of the T. confusum aggregation pheromone. EAG recordings revealed dose-dependent responses to the individual components and increasing responses to the blend and even more to the entire oil. Our study reveals the potential of anethole and the essential oil of V. globosa in the management of stored product pests.

DUST-BORNE TRACE GASES AND ODORANTS The analysis of dust-borne trace gases requires their i-solation from the dust particles. Procedures for the isolation and characterization of trace gases and odorants in the dust from pig houses are given by SCHAEFER et al. (29), HAMMOND et al.(30) and TRAVIS and ELLIOTT (31). Alcoholic solvents were found to be effective for the extraction of volatile fatty ac­ ids and phenols from the dust of hen (32) and pig houses (33), (34). Today, gas chromatography is usually used for the sepa­ ration and identification of the trace gases. Table IV gives a literature review of compounds identified in the dust of pig houses. There are only very few reports on investigations on the dust from hen houses (32). Most of the odours coming from livestock production units are associated with the biological degradation of the animal wastes (35), the feed and the body odour of the animals (1). Volatile fatty acids and phenolic compounds were found to con­ tribute mostly to the strong, typical odour of animal houses by the help of sensory evaluations parallel to the chemical analysis (29),(30). Table V gives quantitative values of volatile fatty acids and phenolic/indolic compounds found in the aerosol phase and in settled dust of piggeries, respectively. The results from the aerosol phase coincide, particularly as far as acetic acid is concerned. For the investigations of the settled dust the coefficients of variation (CV) and the relative values (%) characterizing the percentage of the single compounds as part of the total amount are quoted. The values are corrected with the dry matter content of the dust. Main components are acetic acid and p-cresol, respectively. Table VI compares results from air, dust and slurry in­ vestigations on VFA and phenolic/indolic compounds in piggeries. Relative values are used. When comparing the results derived from investigations on dust, air or slurry it is necessary to use relative values because of the different dimensions, for experience shows that in spite of large quantitative differ­ ences between two samples within the group of carboxylic acids and within the group of phenolic/indolic compounds the propor­ tions of the components remain rather stable (36). In the group of VFA acetic acid is the main component in air, dust, and slurry followed by propionic and butyric acid. The other three acids amount to less than 25%. In the group of phenols/ indoles p-cresol is the main component in the four cited in­ vestigations. However, it seems that straw bedding can reduce the p-cresol content; in this case phenol is the main compo­ nent , i nstead (37 ). 4. EMISSION OF DUST-BORNE VFA AND PHENOLS/INDOLES FROM PIGGERIES The investigations of dust from piggeries show that both VFA and phenols/indoles are present in a considerable amount. However, compared to the air-borne emissions calculated on the base of the results of LOGTENBERG and STORK (38) less than the tenth part (1/10) of phenols/indoles and about the hundredth part (1/100) of VFA are emitted by the dust, only. Table VII compares the dust-borne and air-borne emissions of VFA and

1986 ◽  
pp. 337-337
Keyword(s):  
Fatty Acids ◽  
Acetic Acid ◽  
Volatile Fatty Acids ◽  
Trace Gases ◽  
Matter Content ◽  
Biological Degradation ◽  
Indolic Compounds ◽  
Settled Dust ◽  
Main Components ◽  
Main Component

scholarly journals Judiciary and legal principles for the development of a profile for the profession of detectives of the National Police of Ukraine

2018 ◽  
Vol 68 (1) ◽  
pp. 50-55
Author(s):  
V. P. Ostapovich
Keyword(s):  
Professional Activity ◽  
Occupational Risk Factors ◽  
Legal Principles ◽  
Personal Qualities ◽  
Main Components ◽  
Main Component ◽  
National Police ◽  
Negative Factors ◽  
Theoretical Foundations ◽  
Selection Of

The author has studied the problem of the development of theoretical foundations and methodical tools for conducting job research within the National Police of Ukraine. The author has stated theoretical grounds of creating a profile for the profession of a detective; has revealed the possibilities of using some methods and means of job research for the development of modern profiles of the professions of the system of the National Police of Ukraine. It has been demonstrated that a profile of the profession as a set of parameters characterizing a successful specialist, a professional in a certain field of professional activity, is an important component of the job description. The main component of the profile is the characteristic of psychological peculiarities of professional activity.On the basis of experimental research, the author has formulated the requirements of the profession to the motivational sphere of a specialist, his abilities, temperamental and characterological traits, etc. The main components of the profile of a detective’s profession have been considered. The author has described such structural components of the profile of the profession as general characteristics of the activity, working conditions, negative factors, occupational risk factors, psychological characteristics and professionally important personal qualities of a specialist. The author has provided the demands of the profession to the sensory and perceptual sphere of a detective, general and special abilities, the features of temperament and character, motivation, emotional and volitional qualities. It has been emphasized that comprehensive study of professional police activity based on the development of profiles of the profession is a prerequisite for solving problems related to the efficiency of using personnel potential, optimizing the selection of the most appropriate candidates for the police force, training and retraining of personnel, rationalization of work and reduction of injuries, etc.On the basis of a broad experimental study, the author has established the list of the main professional qualities of a detective of the National Police; has determined the qualitative and quantitative psychological and psychophysiological indicators recommended for the professional activity. The author has also established psychological and psychophysiological contraindications for overtaking the professional activity of a detective (a criminal police officer).

scholarly journals OIL CONTENT AND CHEMICAL COMPOSITION IN THE PARTS OF OIL PALM FRUIT FROM 8 IOPRI VARIETIES

2016 ◽  
Vol 24 (2) ◽  
pp. 67-76
Author(s):  
Sujadi Sujadi ◽  
Hasrul Abdi Hasibuan ◽  
Meta Rivani ◽  
Abdul Razak Purba
Keyword(s):  
Fatty Acid ◽  
Palmitic Acid ◽  
Oil Palm ◽  
Oil Content ◽  
Mean Value ◽  
Oleic Acid Content ◽  
Palm Fruit ◽  
Fruit Samples ◽  
Main Components ◽  
Main Component

Fresh fruit bunches (FFB) consist of fruit be composed grade in few spikelet. Fruit at a spikelet can be distinguished into performed fruit namely internal fruit, middle fruit and outer fruit as soon as each section contain parthenocarpy fruits. This research was conducted for determine composition and content fatty acid of oil at internal fruit, middle, outer and parthenocarpy fruit from oil palm fruit. Samples of fruit came from 3 – 5 spikelet the central of FFB. Result showed that oil content of outer fruit (46.9 + 9.9)% trend higher be compared middle fruit (42.8 + 10.3)% and internal fruit (39.1 + 9.5)%. Parthenocarpy fruits have a low oil content (14.2 + 16.2)% except yellowish fruit trend high relatively oil content. The main components of fatty acid at outer fruit, middle and internal are palmitic acid, oleic, linoleic and stearic with mean value respectively (44.8 – 45.8)%, (37.6 – 38.0)%, (9.9 – 10.9)% and (4.6 – 4.8)%. Oil content at parthenocarpy fruit have amount main component of fatty acid with performed fruit but composition of palmitic acid (40.0 + 5.9)% and oleic (34.6 + 8.4)% lower while linoleic acid (16.9 + 8.5)% and linolenic (1.6 + 1.8)% higher be compared to performed fruit. Simalungun variety has the highest oil content in the part of fruit, with that PPKS 540 and La Mé respectively. PPKS 540 variety has the highest oleic acid content while PPKS 718 has the highest linoleic content.

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